*2.2. Data Sources and Processing*

The data used in this paper mainly includes land use data for 2018 obtained from the Chinese Academy of Sciences Resource and Environmental Science Data Center (https://www.resdc.cn/Default.aspx, accessed on 16 August 2021), with a spatial resolution of 30 m. The data is based on the Landsat 8 remote sensing image of the United States and obtained by manual visual interpretation, and the sampling verification accuracy is above 95%. According to China's land use classification system based on remote sensing monitoring, the land use classification is divided into six categories: cultivated land, forest land, grassland, water area, construction land and unused land. The data processing steps are as follows: firstly, a 300 × 300 m square geographic grid was constructed, superimposed with the current land use data of the study area, and the area of various land types in each geographic grid was calculated. Secondly, according to the evaluation method of the PLEF of land, the production, living and ecological functions of land use types were assigned, respectively, and the values of PLEF of each geographic grid were calculated based on the ArcGIS10.2 software. Thirdly, we used the coupling coordination degree model to

measure the coupling coordination degree among the PLEF and the coupling coordination degree between every two of the PLEF, then, the natural break point classification (Jenks) method was used to divide the coupling coordination degree of the PLEF into three types. Based on the results of the above steps, the PLES was identified. Finally, according to the principle of ecological priority, area dominance and coordinated development, the spatial superposition method to calculate and compare the area size of different functional spaces was used, and the similar types of land were merged to get the optimizing zoning of the PLES.
